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Identification of network topology via quadratic optimization

机译:通过二次优化识别网络拓扑

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Identification of network topology is to estimate the topology of a controllable and observable network with given number of nodes such that the identified network will satisfy the response between specified input and observed output. This paper examines the network topology identification (NTI) problems to find the original graph Laplacian from input-output data. A ‘similar’ set of state-space matrices satisfying the input-output response is firstly constructed through system identification procedure. Based on the similarity relationship, we reformulate the NTI problems as general Quadratically Constrained Quadratic Programming (QCQP) problems. The QCQP problem is then transformed into semidefinite programming (SDP) problem with a rank one constraint. An iterative rank minimization method is proposed to gradually approach the optimal solution. Examples are presented to verify the convergence of the proposed method.
机译:网络拓扑的识别是为了估计具有给定数目的节点的可控和可观察网络的拓扑,以使所识别的网络将满足指定输入和观察到的输出之间的响应。本文研究了网络拓扑识别(NTI)问题,以从输入-输出数据中找到原始图拉普拉斯算子。首先通过系统识别程序构造满足输入输出响应的“相似”状态空间矩阵集。基于相似关系,我们将NTI问题重新表述为一般的二次约束二次规划(QCQP)问题。然后,将QCQP问题转换为具有秩约束的半定规划(SDP)问题。提出了一种迭代秩最小化方法,以逐步逼近最优解。通过实例验证了所提方法的收敛性。

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